Load the necessary library packages prior to loading the data. I used the library(tidyr) and library(dplyr) . This will not show the code in the markdown file output in html.


1. First read the beers data file Beers.csv and inspect the dataframe.
library(readr)
Beers <- read_csv("Beers.csv")
## Parsed with column specification:
## cols(
##   Name = col_character(),
##   Beer_ID = col_double(),
##   ABV = col_double(),
##   IBU = col_double(),
##   Brewery_id = col_double(),
##   Style = col_character(),
##   Ounces = col_double()
## )
head(Beers)
## # A tibble: 6 x 7
##   Name           Beer_ID   ABV   IBU Brewery_id Style                Ounces
##   <chr>            <dbl> <dbl> <dbl>      <dbl> <chr>                 <dbl>
## 1 Pub Beer          1436 0.05     NA        409 American Pale Lager      12
## 2 Devil's Cup       2265 0.066    NA        178 American Pale Ale (…     12
## 3 Rise of the P…    2264 0.071    NA        178 American IPA             12
## 4 Sinister          2263 0.09     NA        178 American Double / I…     12
## 5 Sex and Candy     2262 0.075    NA        178 American IPA             12
## 6 Black Exodus      2261 0.077    NA        178 Oatmeal Stout            12
Beers
## # A tibble: 2,410 x 7
##    Name           Beer_ID   ABV   IBU Brewery_id Style               Ounces
##    <chr>            <dbl> <dbl> <dbl>      <dbl> <chr>                <dbl>
##  1 Pub Beer          1436 0.05     NA        409 American Pale Lager     12
##  2 Devil's Cup       2265 0.066    NA        178 American Pale Ale …     12
##  3 Rise of the P…    2264 0.071    NA        178 American IPA            12
##  4 Sinister          2263 0.09     NA        178 American Double / …     12
##  5 Sex and Candy     2262 0.075    NA        178 American IPA            12
##  6 Black Exodus      2261 0.077    NA        178 Oatmeal Stout           12
##  7 Lake Street E…    2260 0.045    NA        178 American Pale Ale …     12
##  8 Foreman           2259 0.065    NA        178 American Porter         12
##  9 Jade              2258 0.055    NA        178 American Pale Ale …     12
## 10 Cone Crusher      2131 0.086    NA        178 American Double / …     12
## # … with 2,400 more rows
library(readr)
Breweries <- read_csv("Breweries.csv")
## Parsed with column specification:
## cols(
##   Brew_ID = col_double(),
##   Name = col_character(),
##   City = col_character(),
##   State = col_character()
## )
head(Breweries)
## # A tibble: 6 x 4
##   Brew_ID Name                      City          State
##     <dbl> <chr>                     <chr>         <chr>
## 1       1 NorthGate Brewing         Minneapolis   MN   
## 2       2 Against the Grain Brewery Louisville    KY   
## 3       3 Jack's Abby Craft Lagers  Framingham    MA   
## 4       4 Mike Hess Brewing Company San Diego     CA   
## 5       5 Fort Point Beer Company   San Francisco CA   
## 6       6 COAST Brewing Company     Charleston    SC
summary(Beers)
##      Name              Beer_ID            ABV               IBU        
##  Length:2410        Min.   :   1.0   Min.   :0.00100   Min.   :  4.00  
##  Class :character   1st Qu.: 808.2   1st Qu.:0.05000   1st Qu.: 21.00  
##  Mode  :character   Median :1453.5   Median :0.05600   Median : 35.00  
##                     Mean   :1431.1   Mean   :0.05977   Mean   : 42.71  
##                     3rd Qu.:2075.8   3rd Qu.:0.06700   3rd Qu.: 64.00  
##                     Max.   :2692.0   Max.   :0.12800   Max.   :138.00  
##                                      NA's   :62        NA's   :1005    
##    Brewery_id       Style               Ounces     
##  Min.   :  1.0   Length:2410        Min.   : 8.40  
##  1st Qu.: 94.0   Class :character   1st Qu.:12.00  
##  Median :206.0   Mode  :character   Median :12.00  
##  Mean   :232.7                      Mean   :13.59  
##  3rd Qu.:367.0                      3rd Qu.:16.00  
##  Max.   :558.0                      Max.   :32.00  
## 
summary(Breweries)
##     Brew_ID          Name               City              State          
##  Min.   :  1.0   Length:558         Length:558         Length:558        
##  1st Qu.:140.2   Class :character   Class :character   Class :character  
##  Median :279.5   Mode  :character   Mode  :character   Mode  :character  
##  Mean   :279.5                                                           
##  3rd Qu.:418.8                                                           
##  Max.   :558.0
names(Beers)
## [1] "Name"       "Beer_ID"    "ABV"        "IBU"        "Brewery_id"
## [6] "Style"      "Ounces"
names(Breweries)
## [1] "Brew_ID" "Name"    "City"    "State"
Beers <- rename(Beers, Brew_ID = Brewery_id)
names(Beers)
## [1] "Name"    "Beer_ID" "ABV"     "IBU"     "Brew_ID" "Style"   "Ounces"
fullData <- full_join(Breweries, Beers, by = "Brew_ID")
fullData
## # A tibble: 2,410 x 10
##    Brew_ID Name.x   City   State Name.y  Beer_ID   ABV   IBU Style   Ounces
##      <dbl> <chr>    <chr>  <chr> <chr>     <dbl> <dbl> <dbl> <chr>    <dbl>
##  1       1 NorthGa… Minne… MN    Get To…    2692 0.045    50 Americ…     16
##  2       1 NorthGa… Minne… MN    Maggie…    2691 0.049    26 Milk /…     16
##  3       1 NorthGa… Minne… MN    Wall's…    2690 0.048    19 Englis…     16
##  4       1 NorthGa… Minne… MN    Pumpion    2689 0.06     38 Pumpki…     16
##  5       1 NorthGa… Minne… MN    Strong…    2688 0.06     25 Americ…     16
##  6       1 NorthGa… Minne… MN    Parape…    2687 0.056    47 Extra …     16
##  7       2 Against… Louis… KY    Citra …    2686 0.08     68 Americ…     16
##  8       2 Against… Louis… KY    London…    2685 0.125    80 Englis…     16
##  9       2 Against… Louis… KY    35 K       2684 0.077    25 Milk /…     16
## 10       2 Against… Louis… KY    A Beer     2683 0.042    42 Americ…     16
## # … with 2,400 more rows
names(fullData)
##  [1] "Brew_ID" "Name.x"  "City"    "State"   "Name.y"  "Beer_ID" "ABV"    
##  [8] "IBU"     "Style"   "Ounces"
fullData <- rename(fullData, BreweryName = Name.x, BeerName = Name.y)
names(fullData)
##  [1] "Brew_ID"     "BreweryName" "City"        "State"       "BeerName"   
##  [6] "Beer_ID"     "ABV"         "IBU"         "Style"       "Ounces"
fullData %>%
  group_by(State) %>%
  summarise(count = n())
## # A tibble: 51 x 2
##    State count
##    <chr> <int>
##  1 AK       25
##  2 AL       10
##  3 AR        5
##  4 AZ       47
##  5 CA      183
##  6 CO      265
##  7 CT       27
##  8 DC        8
##  9 DE        2
## 10 FL       58
## # … with 41 more rows
BrewStatesC <- Breweries%>%
  group_by(State)%>%
  summarise(count = n())
head(BrewStatesC)
## # A tibble: 6 x 2
##   State count
##   <chr> <int>
## 1 AK        7
## 2 AL        3
## 3 AR        2
## 4 AZ       11
## 5 CA       39
## 6 CO       47
BrewStatesC
## # A tibble: 51 x 2
##    State count
##    <chr> <int>
##  1 AK        7
##  2 AL        3
##  3 AR        2
##  4 AZ       11
##  5 CA       39
##  6 CO       47
##  7 CT        8
##  8 DC        1
##  9 DE        2
## 10 FL       15
## # … with 41 more rows
state.freq <- table(Breweries$State)
barplot(state.freq[order(state.freq)], 
        horiz = T,
        border = NA,
        xlim = c(0, 100),
        main = "Number of Breweries per State",
        xlab = "Number of Brewiews",
        ylab = "States")

#
# Number brewweries in each state:

state.freq
## 
## AK AL AR AZ CA CO CT DC DE FL GA HI IA ID IL IN KS KY LA MA MD ME MI MN MO 
##  7  3  2 11 39 47  8  1  2 15  7  4  5  5 18 22  3  4  5 23  7  9 32 12  9 
## MS MT NC ND NE NH NJ NM NV NY OH OK OR PA RI SC SD TN TX UT VA VT WA WI WV 
##  2  9 19  1  5  3  3  4  2 16 15  6 29 25  5  4  1  3 28  4 16 10 23 20  1 
## WY 
##  4
names(state.freq)
##  [1] "AK" "AL" "AR" "AZ" "CA" "CO" "CT" "DC" "DE" "FL" "GA" "HI" "IA" "ID"
## [15] "IL" "IN" "KS" "KY" "LA" "MA" "MD" "ME" "MI" "MN" "MO" "MS" "MT" "NC"
## [29] "ND" "NE" "NH" "NJ" "NM" "NV" "NY" "OH" "OK" "OR" "PA" "RI" "SC" "SD"
## [43] "TN" "TX" "UT" "VA" "VT" "WA" "WI" "WV" "WY"
View(state.freq)
## Warning in system2("/usr/bin/otool", c("-L", shQuote(DSO)), stdout = TRUE):
## running command ''/usr/bin/otool' -L '/Library/Frameworks/R.framework/
## Resources/modules/R_de.so'' had status 1
sDF<-data.frame(state.freq)
names(sDF)
## [1] "Var1" "Freq"
sDF<- rename(sDF, State = Var1, NoBreweries=Freq)
View(sDF)
## Warning in system2("/usr/bin/otool", c("-L", shQuote(DSO)), stdout = TRUE):
## running command ''/usr/bin/otool' -L '/Library/Frameworks/R.framework/
## Resources/modules/R_de.so'' had status 1
names(Breweries)
## [1] "Brew_ID" "Name"    "City"    "State"


p1 <- plot_ly(Breweries, x = ~State) %>% add_histogram()
p2 <-Breweries %>%
  dplyr::count(State) %>%
  plot_ly(x = ~n, y = ~State) %>%
  add_bars(marker = list(color = 'rgba(170, 17, 19, 0.9)')) %>%
  layout(title = "Number of Breweries by State", 
         legend = list(x = 0.03, y = 1.04)) 
 

subplot(p2)

#